Activation of proteases and changes in Na+‐K+ ATPase subunits in hearts subjected to ischemia‐reperfusion
Bibliographic record
Abstract
Objective To evaluate the role of proteases in sarcolemmal Na + ‐ K + ATPase subunits and activity these ischemia‐reperfusion (I/R) injury by subjecting rat hearts to different times of global ischemia and reperfusion. Methods Global ischemia was induced in rat hearts for 15, 30, and 60 minutes. I/R injury was performed by reperfusing hearts for 5, 10, 20, and 40 minutes after ischemia. Extent of degradation of Na + ‐K + ATPase subunits, α‐1, α‐2, β‐1, and β‐2 was measured in addition to activity assays for Na + ‐K + ATPase, calpain, and MMP‐ 2. Hearts were also perfused with MDL28170 or doxycycline to inhibit calpain or matrix metalloproteinase (MMP)‐2, respectively. Results Global ischemia depressed protein content of β‐1 and β‐2 subunits and activity of Na + ‐K + ATPase which was accompanied by augmented activities of both calpain and (MMPs) and depressed protein content of β‐1 and β‐2 subunits. Calpain and MMP‐2 activities increased whereas activity and protein content for Na + ‐K + ATPase subunits decreased upon reperfusion. MDL28170 was more effective in attenuating the I/R‐induced alterations in cardiac contracture, Na + ‐K + ‐ATPase activity than doxycycline. Conclusions These results show that activation of both calpain and MMP‐2 are involved in depressing Na + ‐K + ATPase activity and degradation of its subunits directly or indirectly in hearts subjected to I/R injury. Funding Manitoba Health Research Council.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".